Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 8,653Sort Recent · Most cited
  1. 2026
    Coresets are more than replay: a data-centric view of continual learningElif Ceren Gok Yildirim, Murat Onur Yildirim, Joaquin VanschorenNeural Computing and Applications · Eindhoven University of Technology
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  2. 2024
    Active Dendrites Enable Efficient Continual Learning in Time-To-First-Spike Neural NetworksLorenzo Pes, Rick Luiken, Federico Corradi, Charlotte FrenkelIEEE 6th International Conference on AI Circuits and Syst… · Eindhoven University of Technology · Delft University of Technology
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  3. 2023
    Continual Learning of Unsupervised Monocular Depth from VideosHemang Chawla, Arnav Varma, Elahe Arani, Bahram ZonoozWACV · Eindhoven University of Technology · TomTom (Netherlands)
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  4. 2021
    Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse NetworksGhada Sokar, Decebal Constantin Mocanu, Mykola PechenizkiySpringer LNCS · Eindhoven University of Technology · University of Twente
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  5. 2021
    Continual Lifelong Learning for Intelligent AgentsGhada SokarIJCAI · Eindhoven University of Technology
  6. 2020
    SpaceNet: Make Free Space For Continual LearningGhada Sokar, Decebal Constantin Mocanu, Mykola PechenizkiyNeurocomputing · Eindhoven University of Technology · University of Twente
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  7. 2020
    Learning Invariant Representation for Continual LearningGhada Sokar, Decebal Constantin Mocanu, Mykola PechenizkiyarXiv · Eindhoven University of Technology · University of Twente
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About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.